The MSCF faculty are key to the success of the MSCF program.

Comprised of individuals ranging from senior faculty members of superior achievement to promising and aggressive junior professionals, all faculty are dedicated to fostering an atmosphere of collaboration and preparation for the MSCF student. Indeed, the stature of the professors teaching in the MSCF course sequence is a highly visible indication of the resources committed to this world-renowned program.

Faculty members also conduct theoretical and applied research. Examples of faculty research include "Robustness of the Black and Scholes Formula" and "A General Framework for Pricing Credit Risk" by Steve Shreve; "Real-Time Queueing Theory" and "Simulation Methods for Option Pricing" by John Lehoczky; and "Equilibrium Forward Curves for Commodities" and "Equilibrium Block Trading and Asymmetric Information" by Duane Seppi. The inter-disciplinary Center for Computational Finance organizes distinguished lectures, seminars and conferences at Carnegie Mellon.

A part of this research is facilitated by leaves of absence or through serving as consultants for business, industry and government. In this way, they are able to pursue the practical implications of quantitative financial theory and, through their accomplishments, help forge the frontiers of quantitative finance.

  • Business & Finance Faculty

    Richard L. Bryant

    Professor Bryant, Adjunct Professor of Industrial Administration, received his BA from Denison University in 1975 and MBA from Carnegie Mellon in 1980. Following six years with H.J. Heinz Company in their Corporate M&A and Treasury areas, Bryant became Reebok International's Treasurer in 1988 and in 1993, Chief Financial Officer of Hefren-Tillotson, a broker/dealer and investment advisor. Professor Bryant joined the Tepper School in 1999 as the Executive Director of Carnegie Mellon's Computational Finance Program and over the years has taught both in Tepper's undergraduate finance program and in the MSCF program.

    Anisha Ghosh

    Anisha Ghosh is an Assistant Professor of Finance at the Tepper School of Business, Carnegie Mellon University. She received her Ph.D. in Economics from the London School of Economics in 2009. Her research lies at the interface of finance and macroeconomics. One part of her research focuses on developing methodologies to assess the empirical plausibility of different classes of pricing models. This lends insights into the strengths and weaknesses of the models and provides guidance for the construction of improved models. The other part of her research uses these insights to build models that explain better several aspects of financial market data. Her research has been published in leading journals, including the Journal of Finance and the Review of Financial Studies.

    Javier Pena

    Javier Pena is the Bajaj Family Professor of Operations Research at the Tepper School of Business, Carnegie Mellon University. He earned his Ph.D. in Applied Mathematics from Cornell University in 1998. His teaching and research interests include financial optimization, machine learning, and convex optimization. Dr. Pena's publications have appeared in journals such as Quantitative Finance, Journal of Risk, Mathematics of Operations Research, and the SIAM Journal on Optimization. Dr. Pena has consulted with Axioma Inc. in the development and implementation of algorithmic tools for portfolio management. Dr. Pena was the recipient of the 2005 George Leland Bach MBA Teaching Award for excellence in the classroom.

    Evelyn Pierce

    Associate Teaching Professor of Business Management Communication with the Tepper School of Business for 22 years, Evelyn completed her terminal degree in 1991 in Fine Arts (Writing) at the University of Pittsburgh. Her research and consulting focuses on the development and implementation of executive problem-solving skills in communications, corporate leadership and communication strategies, cross-team collaboration, and team building. She was honored with the Sustained Excellence in Teaching Award in 2004 as well as the Department of Industrial Management Undergraduate Teaching Award in 1996. She coached the 1998 Grand Prize team at the EDS International Case Competition and has mentored students in their new business development plans and presentations. She regularly consults in Western PA with such companies as PNC Bank, Bayer, Inc., Alcoa, LifeCare Residency Services, and Spann Consulting (contributing to publications for the Robert Woods Johnson Foundation). She also has taught in Carnegie Mellon's Masters of Robotics Systems Development program since its inception in 2011.

    Bryan Routledge

    Bryan Routledge is an Associate Professor of Finance at the Tepper School of Business, Carnegie Mellon University.  He received his Ph.D. from the University of British Columbia in 1996 and a Bachelor of Commerce from Queens University in 1987.  His research focuses on a broad selection of topics in finance. Current research applies quantitative text analysis and natural language processing to economic and financial research questions (e.g, how management discussion and analysis conveys risk, and how Twitter can track public opinion).  Other recent research investigates the quantitative properties of asset prices and macroeconomics such as the positive correlation of asset returns with future economic growth and understanding the connection between risk attitudes and asset pricing dynamics, and the risk premia of commodity prices.  He is an associate editor at the Journal of Quantitative Finance and the Critical Review of Finance and current Secretary Treasurer of the Western Finance Association. Teaching includes "Corporate Finance," "Private Equity and Venture Capital", and "Alpha: Implementing Quantitative Strategies."

    Duane J. Seppi

    BNY Mellon Professor of Finance at the Tepper School of Business. Received his Ph.D. from the University of Chicago in 1988. His teaching and research interests include energy and commodity derivatives, stochastic volatility modeling, market microstructure, limit orders, and liquidity. His research has been published in the Review of Financial Studies, Journal of Finance, Journal of Financial Economics and other leading finance and economics journals. He has been on the editorial boards of the Journal of Finance, the Review of Financial Studies, the Journal of Financial Markets, and the Review of Finance. He was a visiting scholar at the US Securities and Exchange Commission and at Nanyang Business School.

    Richard O. Young

    Teaching Professor in Management Communication received his Ph. D. from Carnegie Mellon University in 1989 with a dissertation on the differences between expert and novice management consultants. Since then, he has served as a management consultant for a number of U.S. firms and start-ups. Dr. Young's research is focused on conflict resolution and on the decision-making expertise of the audiences of managers. He has presented many papers at national conferences. He is the author of How Audiences Decide: A Cognitive Approach to Business Communication, New York: Routledge, 2011.

    Ariel Zetlin-Jones

    Ariel Zetlin-Jones is an Assistant Professor of Economics at the Tepper School of Business, Carnegie Mellon University. He received his Ph.D. from the University of Minnesota in 2012 and a Bachelor of Arts from Williams College in 2004. Ariel's research focuses on the interaction of finance and the macroeconomy, including an examination of the causes of financial crises and the quantitative effects of disturbances in financial markets on broader economic activity. Ariel's research on the nature of collapses in secondary loan markets (e.g., the market for mortgage-backed securities) was recently published in the American Economic Review. Additionally, Ariel is a co-organizer of the Tepper-LAEF "Advances in Macro-Finance" Conference.

  • IT Faculty

    John K. Ostlund

    John K. Ostlund was most recently Principal Research Programmer at the Auton Lab, a leading Machine Learning research lab at Carnegie Mellon University. He was there for almost a decade, working primarily with C and C++ on machine learning algorithms and the application of large data sets from U.S. government agencies involved in intelligence, health monitoring and fleet maintenance. Prior to that, John was a leading course author and instructor for Learning Tree International, a top-ranked technology and management training company, with courses in C++, C, Unix, Linux and Solaris. He holds an MS in Computational Finance from Carnegie Mellon University and a BA in Physics and Mathematics from St. Olaf College.

    Stephen Roehrig

    Teaching Professor of Information Systems and Public Policy. He received his Ph.D. in 1992 from the University of Pennsylvania. His teaching interests include object-oriented programming and program design, uncertain reasoning, database confidentiality and evolutionary programming. Dr. Roehrig's current research applies mathematical programming and probabilistic methods to database confidentiality protection and intelligent databases. He has consulted for a number of government agencies such as the Bureau of the Census, Bureau of Labor Statistics and Executive Office of the President (Office of Management and Budget). Dr. Roehrig has an extensive list of publications in journals such as Operations Research, Management Science, and the Journal of Official Statistics.

  • Math Faculty

    William J. Hrusa

    Professor of Mathematical Sciences, Dr. Hrusa earned his Ph.D. from Brown University.  His main areas of research are in partial differential equations, integral equations, and calculus of variations with particular emphasis on problems that arise in continuum mechanics. Current research is focused on Lavrentiev’s phenomenon in the calculus variations, i.e. with situations in which the infimum for a given variational problem is sensitive to the precise degree of regularity that is assumed for the competing functions. A major goal is to understand if this phenomenon can occur for realistic problems in nonlinear elasticity.

    Dmitry Kramkov

    Mellon College of Science Professor of Mathematical Finance, Professor Kramkov earned his Ph.D. from the Steklov Mathematical Institute in Moscow in 1991. His current research is mainly focused on topics in mathematical finance such as equilibrium, dynamic game theory, option pricing theory, and optimal investment. In 1996 he received a prize of the Second European Congress of Mathematics in Budapest for his research on statistics and mathematical finance. From 1997 to 2000 Dr. Kramkov worked for Tokyo-Mitsubishi International in London, where he was the Acting Head of Research and Product Development. His main responsibility was the evaluation of complex derivative contracts. Dr. Kramkov currently serves as an Associate Editor of the journal of Finance and Stochastics. He has an affiliation with the University of Oxford, where he is a member of Man-Oxford Institute for Quantitative Finance.

    Kasper Larsen

    Associate Professor of Mathematical Sciences with a background in Mathematical Economics from the University of Southern Denmark. Dr. Larsen's research interests are mainly how mathematical tools can be applied to solve problems from finance and economics. The main research focus is utility theory and various applications hereof such as model stability and equilibrium price formation. His work has been published in journals such as the Mathematical Finance, Finance and Stochastics, Annals of Applied Probability, and Journal of Economic Theory.

    Roy A. Nicolaides

    Professor of Mathematical Sciences, Ph.D. from the University of London. Professor Nicolaides' research and teaching interests include applications of partial differential equations to mathematical finance and other fields.  He serves or has served on the editorial boards of the Journal of Computational Finance, the SIAM Journal of Scientific Computing, the Journal of Computational Fluid Dynamics, and other journals. Professor Nicolaides teaches the MSCF course on numerical methods for partial differential equations, which he has done since the program began in 1994.

    Scott Robertson

    Assistant Professor of Mathematical Sciences, Professor Robertson earned his Ph.D. from Boston University. His research focuses on using the theory of Large Deviations to solve problems of optimal investment and options pricing in Mathematical Finance.  Prior to attending graduate school, Professor Robertson worked for four years as an analyst in the Fixed-Income research departments at both Citigroup and Fidelity Investments.  Professor Robertson's papers have been published in Mathematical Finance, Finance and Stochastics, and the Annals of Applied Probability.

    Steven Shreve

    Orion Hoch and University Professor of Mathematical Sciences and member of the MSCF Steering Committee. Professor Shreve earned his Ph.D. in 1977 from the University of Illinois.  His research and teaching interests range from capital asset pricing models to various aspects of mathematical finance, including the effect of transaction costs and unknown volatility on option prices and diffusion models of limit-order books.  Dr. Shreve is past-President of the Bachelier Finance Society. In 1994, Dr. Shreve was one of the founders of the Carnegie Mellon Master's program in Computational Finance.  Dr. Shreve serves as Advisory Editor of the journal, "Finance and Stochastics." He has co-authored a number of books, including "Brownian Motion and Stochastic Calculus" and "Methods of Mathematical Finance." He has written a two-volume work based on his teaching in the MSCF program, "Stochastic Calculus for Finance."

  • Statistics Faculty

    Max G'Sell

    Assistant Professor of Statistics, received his Ph.D. in statistics from Stanford University in 2014.  Dr. G'Sell's research interests involve a variety of theoretical and applied questions in high dimensional statistics and machine learning.

    John P. Lehoczky

    Thomas Lord University Professor of Statistics and Mathematical Sciences received his Ph.D. in statistics from Stanford University in 1969. Dr. Lehoczky's main teaching and research interests involve the theory and application of stochastic processes to model the behavior of real applications. Over the last five years, Dr. Lehoczky has focused on two broad application areas: financial markets and real-time computer systems. In finance, he has been involved in the development of new simulation methodologies to price and hedge complex securities. More recently, Dr. Lehoczky has been focusing on the estimation of parameters of stochastic differential equations and its application to term structure or asset price process models. His research in real-time computer systems involves collaboration with researchers at the CMU School of Computer Science, Software Engineering Institute, Electrical and Computer Engineering Department and the Department of Mathematical Sciences. Dr. Lehoczky is developing, jointly with Professor Steve Shreve, a new analytic methodology called real-time queuing theory, which predicts the ability of a queuing system to satisfy the timing requirements of the tasks, which use it. The theory is being implemented and tested on several pilot systems at CMU. He has been published extensively in a variety of journals including Annals of Applied Probability, Management Science, and Real-Time Systems and Dr. Lehoczky has served on the editorial staff of Management Science, IEEE Transactions on Computers, and Real Time Systems.

    Chad Schafer

    Associate Professor of Statistics, received his Ph.D. in statistics from the University of California, Berkeley in 2004. His primary research interests focus on addressing inference problems in the physical sciences using novel, often computationally- intensive, statistical methods. He is a part of the McWilliams Center for Cosmology at CMU and actively collaborates with researchers in astronomy, particle physics, and risk assessment.  He has published in the Journal of the American Statistical Association and the Astrophysical Journal, among others.

    Mark J. Schervish

    Professor of Statistics, received his Ph.D. in statistics from the University of Illinois in 1979. Dr. Schervish's main research interests involve the foundations of inference, the theory and application of Gaussian processes, and modeling of financial data. Dr. Schervish has collaborated with researchers in Civil, Mechanical, and Electrical Engineering on statistical modeling of real-world processes. Dr. Schervish has published a number of books and many articles in journals such as Journal of the American Statistical Association, The Annals of Statistics, Biometrika and others.

  • Adjunct Faculty

    Robert Almgren

    Robert Almgren, co-founder of Quantitative Brokers, providing agency algorithmic execution and cost measurement in futures and fixed income. Until 2008, Dr Almgren was a Managing Director and Head of Quantitative Strategies in the Electronic Trading Services group of Bank of America. From 2000-2005, he was a tenured Associate Professor of Mathematics and Computer Science at the University of Toronto, and Director of its Master of Mathematical Finance program. Before that, he was an Assistant Professor of Mathematics at the University of Chicago and Associate Director of the Program on Financial Mathematics. Dr. Almgren holds a B.S. in Physics and Mathematics from the Massachusetts Institute of Technology, an M.S. in Applied Mathematics from Harvard University and a Ph.D. in Applied and Computational Mathematics from Princeton University. He has an extensive research record in applied mathematics, including papers on optimal trading, transaction cost measurement, and portfolio construction.

    Leif Andersen

    Leif B. G. Andersen is the Global Co-Head of the Quantitative Strategies Group at Bank of America Merrill Lynch. He holds MCs in Electrical and Mechanical Engineering from the Technical University of Denmark, an MBA from University of California at Berkeley, and a Ph.D. in Finance from Aarhus Business School. He was the co-recipient of Risk Magazine's 2001 Quant of the Year Award, and has worked for more than 20 years as a quantitative researcher in the derivatives pricing and risk management areas. He has authored influential research papers and books in all areas of quantitative finance, and is an associate editor of Journal of Computational Finance.

    Peter Cai

    Peter Cai, is Chief Risk Officer of Global Atlantic Financial Group. Until recently, he was a managing director at Morgan Stanley in charge of portfolio risk management and stress testing. Peter also worked as a risk strategist in the Fixed Income division at Lehman Brothers and as the global director of consulting at Askari, a boutique risk solutions firm. Peter holds a Ph.D. in Materials Science from Pennsylvania State University and the Financial Risk Manager (FRM) and Professional Risk Manager (PRM) certifications.


  • Guest Lecturers

    Devin Anderson

    Devin Anderson is a director in equity derivative sales at Deutsche Bank, specializing in advising and facilitating asset manager and hedge fund trading. He works closely with clients to develop hedging programs, express market views and interpret market sentiment from equity derivative implied prices. He has extensive experience in synthetic equity products and options, as well as over-the-counter volatility, dividend and correlation derivatives. Devin joined Deutsche Bank in 2006. He holds a Bachelor of Finance from the University of Pittsburgh and an MBA from Carnegie Mellon.

    Dave Korpi

    Dave Korpi is an interest rate derivatives trader at Goldman Sachs. Prior to joining Goldman Sachs, he was at Deutsche Bank for nine years, where he traded a variety of interest rate products, including options, callable agency debt and swaps. Dave holds a Bachelor of Science degree in Computational Finance from Carnegie Mellon, and has provided advice on trading to students at Carnegie Mellon since 2011.

    Michael Mendelson

    Michael Mendelson, principal, is director of Global Trading Research at AQR Capital Management, a Greenwich-based quant investment management firm. AQR’s investments span from aggressive high volatility market-neutral hedge funds to low volatility benchmark-driven traditional products. Prior to joining AQR in 2005, Michael worked at Goldman Sachs where he was MD and Head of Quantitative Trading and served on the Equities Division Risk Committee and as co-chair of the Systems Risk Taskforce. Michael received an Master of Science in Chemical Engineering from MIT, along with an Bachelor of Science in Chemical Engineering; a Bachelor of Science in Mathematics; and a Bachelor of Science in Management. Michael has his MBA from the University of California at Los Angeles.

    Giles Nugent

    Giles Nugent is EVP and head of front office technology for PIMCO in their New York office. Prior to joining PIMCO in 2011, Giles owned his own software development company. Previously, Giles worked for twenty years in research and technology organizations on Wall Street. Most recently, he was head of structured products technology at Bank of America for six years where he also worked on the bank's mergers with Countrywide and Merrill Lynch. For eight years prior to that, he worked at Goldman Sachs in mortgage research, developing applications and supporting the mortgage trading desk, and at Salomon Brothers for five years in mortgage research. Giles holds an MBA from Duke University and a Bachelor of Art in mathematical sciences from the University of North Carolina.

    Giuseppe Nuti

    Giuseppe Nuti is currently the head of Fixed Income trading at UBS New York. He has worked as a trader for over fifteen years, initially in the interest-rates options and swaps market and, since 2006, in the European and US Government bond markets algorithmic trading, where he specialized in high frequency strategies at KCG and Citadel, before joining UBS in 2014. His research interests are in algorithmic trading, numerical solutions to Bayesian inference, and interaction between market participants in price-setting microstructure. He holds a Ph.D in Computer Science with particular focus on Markov Decision Processes applied to finance and an MSc in financial mathematics from City University, London.

    Paul Russo

    Paul Russo is global co-COO of the Equities Franchise at Goldman Sachs, serving on the Firmwide Risk Committee, Firmwide New Activity Committee and Securities Division Executive Committee. Paul joined Goldman in 1989 in US Equity Derivatives where he was responsible for the Portfolio Trading and the Index Volatility businesses. In 1997, Paul moved to Hong Kong to run non-Japan Asia Equity Derivatives. In 2000, he transferred to co-head the Fixed Income, Currency and Commodities Division in non-Japan Asia and in 2002, moved to the Equities Division in London to head the Equity Derivatives business in Europe. Paul was named Partner in 2000. Paul earned an MBA from the University of Chicago in 1990 and a Bachelor of Science from Carnegie Mellon in 1986.

    Reha Tutuncu

    Reha Tutuncu is a member of the Global Stock Selection group at AQR Capital Management, where he focuses on implementation and optimization research. Prior to AQR, he was a Managing Director in the Quantitative Investment Strategies Group at Goldman Sachs Asset Management. Earlier, he was an Associate Professor at Carnegie Mellon University. He is a co-author of the book Optimization Methods in Finance and a member of the editorial board of the Journal of Computational Finance. Reha earned a B.S. in industrial engineering from Bilkent University and an M.S. and Ph.D. in operations research and industrial engineering from Cornell University.

    David Vener

    David Vener is a director on the Credit Structuring and Bank Solutions Desk at BNP Paribas. David's transactional experience includes collateralized loan obligations, mortgage re-securitizations, structured funding and various types of credit derivatives including corporate synthetic collateralized debt obligations. David has a Bachelor of Science in Applied Mathematics and Physics from Georgia Tech, and a Ph.D. in Applied Mathematics from the Massachusetts Institute of Technology.